Oracle has introduced a new AI-native builder experience that increases the pool of organizations that can create and run agentic applications.
The announcement extends Oracle’s push beyond embedded AI assistants and standalone agents toward outcome-driven applications that can coordinate tasks, trigger workflows, follow approvals, and execute actions within existing enterprise systems.
CX leaders must now consider whether AI can reliably support and execute business processes within existing operational environments.
Chris Leone, Executive Vice President, Applications Development at Oracle, explained that the new builder experience reflects a broader shift toward enterprise applications that can actively coordinate and execute outcomes.
“Enterprise software is moving beyond systems that record work to systems that actively drive and execute outcomes,” he said.
“With this new builder experience, customers and partners can build Fusion Agentic Applications that are backed by specialized agent teams and run natively inside Oracle Fusion Applications, where the business objects, workflows, security, approvals, and auditability already exist.”
CX Needs Operational Alignment
Many organizations have moved quickly to adopt AI; however, successful proofs of concept have not always translated into production-ready transformation.
While generative AI can improve content creation and customer interactions, many organizations still struggle to deploy AI consistently across day-to-day operations at enterprise scale, as many tools operate outside of customer work.
Quality CX depends on coordinated processes, meaning if AI is disconnected from these systems, it may provide recommendations but cannot complete task accurately or within business guidelines, creating fragmented automation.
Disconnected AI also raises governance concerns, so as organizations move toward agentic AI, these safeguards become more important as expectations move toward the technology executing work safely and transparently.
As a result, improving CX depends less on deploying another AI interface and more on orchestrating workflows across enterprise systems, data, teams, and governance frameworks that ultimately determine customer outcomes.
Oracle’s Fusion AI Play
Oracle has introduced an AI-native builder experience for Oracle AI Agent Studio that enables customers and partners to create and run Fusion Agentic Applications directly inside Oracle Fusion Applications.
These applications combine teams of specialized AI agents that can reason and execute work using Fusion business objects, workflows, approvals, policies, and audit logs.
To help organizations move their AI automations from experimentation to production, Oracle’s approach embeds both the development environment and runtime within Fusion Applications, allowing organizations to build AI capabilities that automatically inherit the platform’s existing models and processes.
By positioning Fusion as both the system of record and the system where AI-powered work is executed, this broadens the scope into who can build enterprise AI applications.
For example, business users can use no-code and natural language tools, while developers can use professional coding environments, all within the same governed platform.
By enabling both technical and non-technical users to build AI applications within the same governed environment, Oracle aims to reduce development bottlenecks and accelerate enterprise AI adoption without requiring organizations to compromise security or consistency.
Rethinking CX Automation Value
For CX leaders, Oracle’s announcement reflects a broader shift in how AI should create business value, coordinating multiple activities across business processes to achieve a specific outcome.
Moving away from simply assisting a service agent, AI can improve services by reducing escalations, accelerating resolution, and support revenue operations across customer-facing teams.
This shift for the competitive landscape means enterprise AI expectations are now focusing on business applications where customer, financial, operational, and employee data already reside.
Those that can embed AI directly into these platforms can enable it to access enterprise data, execute workflows, and operate within established frameworks.
Speaking with CX Today, Martin Taylor, Co-Founder and Deputy CEO of Content Guru, argued that successful AI adoption depends on enhancing the business processes organizations have already refined over decades.
“CX builds on 40 years of process evolution, these are business processes that have been honed and evolved since the 1980s when the first call centers were introduced,” he noted.
“It’s using the best adapted business processes and then applying automation to those.”
For CX leaders assessing current vendor offerings, the challenge is assessing where AI can remove friction from the end-to-end customer journey.
With many customer experience issues originating in back-office operations rather than customer-facing interactions, delayed and fragmented operations shape the experience.
As a result, organizations should evaluate AI based on its ability to coordinate work across departments and improve measurable business outcomes, as the greatest opportunity may lie in using governed AI to address the obstacles that determine loyalty and satisfaction.
